2026年自己招一个ai员工-Ubuntu22.04安装Openclaw详细教程-小白可直接上手-持续更新中

自己招一个ai员工-Ubuntu22.04安装Openclaw详细教程-小白可直接上手-持续更新中p p h4 id ubuntu2204 E5 AE 89 E8 A3 85openclaw Ubuntu22 04 安装 Openclaw h4 ul li 准备工作 ul li 一键安装 li li 设置通道 配置飞书 lt li ul li ul

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Ubuntu22.04安装Openclaw

  • 准备工作
    • 一键安装
    • 设置通道 配置飞书
  • 让ai员工更好用
    • 加入免费的模型
    • 配置钉钉
    • 在GLM-4 .7-Flash基础上加入deepseek
    • 加入minimax和豆包模型
    • 配置web搜索
      • .env File
    • 🔌 Exa MCP Server for OpenAI Codex
    • Quick Start
      • cURL
    • Function Calling / Tool Use
      • OpenAI Function Calling
      • Anthropic Tool Use
    • Search Type Reference
    • Content Configuration
    • Domain Filtering (Optional)
    • Web Search Tool
    • Category Examples
      • People Search (`category: "people"`)
      • Company Search (`category: "company"`)
      • News Search (`category: "news"`)
      • Research Papers (`category: "research paper"`)
      • Tweet Search (`category: "tweet"`)
    • Content Freshness (maxAgeHours)
    • Other Endpoints
    • Troubleshooting
    • Resources

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curl -fsSL https://clawd.org.cn/install.sh | sudo bash

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可以重新启动openclaw,执行openclaw-cn gateway restart

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  1. MiniMax M2.5 API Key获取访问MiniMax平台:https://api.minimax.chat/;
    注册/登录账号,直接获取API Key,复制保存备用。



  2. Seedance2.0 API Key获取访问火山方舟平台:https://console.volcengine.com/ark;
    注册/登录火山引擎账号,开通“火山方舟”服务;
    在“API Key管理”页面创建Key,复制保存备用。
    之后配置openclaw.json
    就可以接入多个大模型了。
























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GPT plus 代充 只需 145

.env File

 
  
    
    

Give OpenAI Codex real-time web search, code context, and company research with Exa MCP.

Run in terminal:

GPT plus 代充 只需 145

Tool enablement (optional):
Add a query param to the MCP URL.



Enable specific tools:

 
     

Enable all tools:

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Your API key:
Manage keys at dashboard.exa.ai/api-keys.



Troubleshooting: if tools don’t appear, restart your MCP client after updating the config.

📖 Full docs: docs.exa.ai/reference/exa-mcp


cURL

 
      

Function calling (also known as tool use) allows your AI agent to dynamically decide when to search the web based on the conversation context. Instead of searching on every request, the LLM intelligently determines when real-time information would improve its response—making your agent more efficient and accurate.

Why use function calling with Exa?

  • Your agent can ground responses in current, factual information
  • Reduces hallucinations by fetching real sources when needed
  • Enables multi-step reasoning where the agent searches, analyzes, and responds

📚 Full documentation: https://docs.exa.ai/reference/openai-tool-calling

OpenAI Function Calling

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Anthropic Tool Use

 
       
Type Best For Speed Depth Real-time apps, autocomplete, quick lookups Fastest Basic Most queries - balanced relevance & speed Medium Smart Research, enrichment, thorough results Slow Deep Complex research, multi-step reasoning Slowest Deepest

Tip: works well for most queries. Use when you need thorough research results or structured outputs with field-level grounding.


Choose ONE content type per request (not both):

Type Config Best For Text Full content extraction, RAG Highlights Snippets, summaries, lower cost

⚠️ Token usage warning: Using (full page text) can significantly increase token count, leading to slower and more expensive LLM calls. To mitigate:

  • Add limit:
  • Use instead if you don’t need contiguous text

When to use text vs highlights:

  • Text - When you need untruncated, contiguous content (e.g., code snippets, full articles, documentation)
  • Highlights - When you need key excerpts and don’t need the full context (e.g., summaries, Q&A, general research)

Usually not needed - Exa’s neural search finds relevant results without domain restrictions.

When to use:

  • Targeting specific authoritative sources
  • Excluding low-quality domains from results

Example:

GPT plus 代充 只需 145

Note: and can be used together to include a broad domain while excluding specific subdomains (e.g., ).


 
     

Tips:

  • Use for most queries
  • Great for building search-powered chatbots or agents
  • Combine with contents for RAG workflows

Use category filters to search dedicated indexes. Each category returns only that content type.

Note: Categories can be restrictive. If you’re not getting enough results, try searching without a category first, then add one if needed.

People Search ()

Find people by role, expertise, or what they work on

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Tips:

  • Use SINGULAR form
  • Describe what they work on
  • No date/text filters supported

Company Search ()

Find companies by industry, criteria, or attributes

 
      

Tips:

  • Use SINGULAR form
  • Simple entity queries
  • Returns company objects, not articles

News Search ()

News articles

GPT plus 代充 只需 145

Tips:

  • Use livecrawl: “preferred” for breaking news
  • Avoid date filters unless required

Research Papers ()

Academic papers

 
      

Tips:

  • Use type: “auto” for most queries
  • Includes arxiv.org, paperswithcode.com, and other academic sources

Tweet Search ()

Twitter/X posts

GPT plus 代充 只需 145

Tips:

  • Good for real-time discussions
  • Captures public sentiment

sets the maximum acceptable age (in hours) for cached content. If the cached version is older than this threshold, Exa will livecrawl the page to get fresh content.

Value Behavior Best For 24 Use cache if less than 24 hours old, otherwise livecrawl Daily-fresh content 1 Use cache if less than 1 hour old, otherwise livecrawl Near real-time data 0 Always livecrawl (ignore cache entirely) Real-time data where cached content is unusable -1 Never livecrawl (cache only) Maximum speed, historical/static content (omit) Default behavior (livecrawl as fallback if no cache exists) Recommended — balanced speed and freshness

When LiveCrawl Isn’t Necessary:
Cached data is sufficient for many queries, especially for historical topics or educational content. These subjects rarely change, so reliable cached results can provide accurate information quickly.



See maxAgeHours docs for more details.


Beyond , Exa offers these endpoints:

Endpoint Description Docs Get contents for known URLs Docs Q&A with citations from web search Docs

Example - Get contents for URLs:

 
        

Results not relevant?

  1. Try - most balanced option
  2. Try - runs multiple query variations and ranks the combined results
  3. Refine query - use singular form, be specific
  4. Check category matches your use case

Need structured data from search?

  1. Use or with
  2. Define the fields you need in the schema — Exa returns grounded JSON with citations

Results too slow?

  1. Use
  2. Reduce
  3. Skip contents if you only need URLs

No results?

  1. Remove filters (date, domain restrictions)
  2. Simplify query
  3. Try - has fallback mechanisms

  • Docs: https://exa.ai/docs
  • Dashboard: https://dashboard.exa.ai
  • API Status: https://status.exa.ai

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